AI/ML Platform Engineer

Location: Brazil
Employment Type: Contract
Work Model: Remote

Role Overview

We are seeking an experienced AI/ML Platform Engineer to design, build, and maintain scalable AI/ML infrastructure and delivery platforms. The ideal candidate will have hands-on experience supporting GPU workloads, LLM integrations, Kubernetes, Docker, Helm, AWS, Terraform/Ansible, CI/CD, and DevOps tooling.

Key Responsibilities

• Design and engineer scalable infrastructure for AI/ML workloads and GPU-based environments.
• Build and maintain platforms supporting LLM applications and integrations.
• Deploy and manage AI/ML workloads using Kubernetes, Docker, and Helm.
• Develop and maintain CI/CD pipelines for ML models, applications, and infrastructure.
• Automate infrastructure provisioning and configuration using Terraform and Ansible.
• Deploy and manage AI/ML infrastructure on AWS.
• Implement monitoring, logging, security, and performance optimization for AI/ML platforms.
• Support model deployment, integration, scaling, and operationalization.
• Troubleshoot infrastructure, container, Kubernetes, and deployment issues.
• Establish DevOps and MLOps best practices for reliable AI/ML delivery.
• Collaborate with data scientists, ML engineers, software engineers, and DevOps teams.

Required Skills

• Strong experience as an AI/ML Platform Engineer, MLOps Engineer, or DevOps Engineer supporting AI/ML platforms.
• Hands-on experience with:
  • Kubernetes
  • Docker
  • Helm
  • AWS
  • Terraform and/or Ansible
  • CI/CD
  • GPU workloads
  • LLM integrations
• Strong understanding of cloud infrastructure, containers, orchestration, and automation.
• Experience building scalable and highly available AI/ML platforms.
• Strong scripting and automation skills.
• Knowledge of monitoring, logging, security, and infrastructure optimization.

Preferred Skills

• Experience with MLOps platforms and practices.
• Experience with NVIDIA GPU infrastructure and CUDA environments.
• Knowledge of Python and AI/ML frameworks.
• Experience with LLM platforms, model serving, and inference workloads.
• Familiarity with AWS services such as EKS, EC2, S3, and SageMaker.
• Experience with Prometheus, Grafana, or similar observability tools.